WEBVTT
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>> Hello, my name is
Noelle LaCharite and welcome
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to another episode of
This Week In Cognitive,
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where we are going to talk
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through all the different
ways that you can learn by
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doing with Cognitive Services and
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really a bunch of
different things in Microsoft AI.
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So first, I always like
to remind you of some of
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the pre-built models that are
available at your disposal.
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Some of our other episodes have
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talked through this in more detail,
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so feel free to go back
and take a look at those.
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But today, we're going to take
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a look at a bunch of
different samples.
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All the different ways that you can,
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across different properties
in Microsoft AI,
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learn by implementing projects
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that had been built by
other engineers and shared with you.
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These are available all
over the place from GitHub,
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to different galleries
within Microsoft,
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and so I'm going to
just take a few moments
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and share those with you.
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So, the first stop on this tour
of all the things you can learn
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by actually building projects
yourself is inside of our samples.
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If you go out to GitHub,
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and you'll see this link in
the description of the video.
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But if you go to
GitHub, you can go to
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Azure samples and in
this organization,
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you will see a ton of samples.
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We want to actually refine
the search a little bit.
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So, I would have you go in and
type in "Cognitive Services."
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Once you have "Cognitive
Services," you'll
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see a bunch of
specific samples show up.
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I will call your attention.
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Remember in a previous episode,
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we talked about using
speech-to-text and
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text-to-speech to you're
see these projects there,
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but I'm actually going to show
you a couple very specific ones
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that my team has created and
I'm super excited about.
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One is called Studybot.
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Now the Studybot sample,
and you'll see it here,
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it's in C# that we're
working on building it
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across all of our primary languages.
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But this sample allows
you to go and just see
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a typical rather
complex combination of
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Cognitive Services that
are built in order to
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create a standard intelligent agent.
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If you're looking for
an example that you can go
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and just take this code
and start from there.
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You know a lot of times,
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we suffer from my blank space
or blank page syndrome, right?
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Where we're like, "Oh my gosh,
how do I even just get started?"
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So, these projects are built
for exactly that purpose.
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We have found, based on a lot
of the data that we've gotten,
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that customers are looking
to build intelligent agents.
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So, this is an incredibly
useful skill for
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you to develop and
you can do that just
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by building some of these samples,
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and diving into the code,
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and all of that code
is available here.
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A lot of our samples,
you'll also see,
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they come with a nice ReadMe file
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that'll tell you how
to use the sample,
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what's in each folder,
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and some descriptions are on what
we did and what we tried to do.
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Now remember, these are samples
so they're not meant to be
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the golden use case of
how to do everything.
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It's just a chance for you
to get started quickly,
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build something meaningful
and something that
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you can translate to the enterprise.
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So, another example of services
I wanted to also show you,
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can be found in AI School.
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Now AI School is more like
a training curriculum, right?
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Your ability to go in
and take some classes.
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There's lots of different
ways to do this.
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Some of them are
Cognitive Services so if
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you wanted to really
dive deep and get
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a full blown application
development experience
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in using Cognitive Services
or Cognitive Search or bots,
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you can actually build
an intelligent agent or
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build a Computer Vision application
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all within the context of
some of these courses.
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They are much longer, right?
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With some of these samples,
you can just go to
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Github,clone the repo and
get going right away.
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These are a little bit longer,
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they're usually hours
of time invested.
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But the benefit of that is
that you are handheld a
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little bit more than you
would be with a GitHub repo.
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You're also provided
the step-by-step guide,
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and then on top of that,
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it usually is much
more in depth, right?
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We go through multiple scenarios
within a single class.
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So, a really great opportunity
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for you to go and take a look at it.
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You can see some of
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these applications are built
out like Conversational AI,
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huge opportunity in our
industry right now.
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Every company is looking
for ways to build
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Conversational AI into
the applications that they have,
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but you also see machine-learning and
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intelligent edge. All things, right?
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Worth your investment.
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Dive into it, start building.
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If you feel super comfortable in it,
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maybe you can just build
a sample from GitHub,
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but if not, if you need
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a little bit more guidance or
maybe a lot more guidance,
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these classes will help you.
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Now another thing, another area
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when I found it I was like,
"This is incredible."
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I think some of you might
remember that I had shared
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with you the architecture
of Microsoft AI, right?
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Sometimes, we want to use
pre- built models and actually,
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anytime we can use a pre- built
model, we want to do that.
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But then on the other side,
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there are some problems that
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we really need to build
our own model for, right?
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We want to maybe build something
that no one's ever built before.
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Built-in in a way that's very
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very specific to
our business or industry.
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So, machine learning allows us to do
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that and the gallery which
I am showing to you now,
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allows you to see project examples
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that are built already
that you can, again,
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allows you to start
rather than from scratch,
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you can actually start
with an existing project.
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So, if you go in here,
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one of the nice things
I like about it,
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which I want to just
point your attention to,
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is that you can search by industry.
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So, our goal as Microsoft and
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as the engineer's building
the samples for you,
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is to fill up each one
of these buckets, right?
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Retail, manufacturing,
banking, health care,
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how can we make it easier
for you to get started?
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So, we're looking to build scenarios,
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place them in here.
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Whether they're using
pre-built models,
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which you'll see those in
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our samples and GitHub and
maybe in the AI School,
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or for the machine learning models
you're building from scratch.
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We will build
these AI Galleries right
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up projects within
the gallery that allow
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you to start with a model that
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will speed up your ability
to develop something.
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Now, there's lots of opportunities
you'll see here on this page.
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There's tutorials that
you can download,
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that'll walk you step-by-step
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through building
a model from scratch.
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Or you can take
an existing model and just
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augment it if you're already
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experienced in how to
do it step-by-step.
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So, we try to meet you where you are,
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where your experiences
in order to give you
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the full breadth of learning, right?
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I am a huge fan of learning
by doing, I think.
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If you can build a bunch
of samples and create
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some muscle memory around
either creating a model,
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or using a pre-built model or
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a collection of pre-built
models together,
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that's how you're really going to
be able to impact your business.
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So, I really encourage you in order
to start building immediately,
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now you've got
some pretty decent tools
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The last one I want to show you is
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where some of
our most fun projects are.
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You'll remember this from
some of the things that
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we've done in the past, right?
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We have the AI Lab.
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AI Lab is home to the JFK Files
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which we've seen before and you
probably have seen on the AI Show,
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but it's also home to a bunch
of other cool projects.
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The reason that I
love these projects,
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is that kind of a philosophy of
mine is if I demo something,
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if I go on stage or if I
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demonstrate in a hackathon
how to do something,
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I want to make sure there's
a GitHub Repo to back it up.
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That the source files are
available to you as a def.
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So, you can see here.
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Look at all these really
cool projects these
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are Snip Insights one of my favorite.
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Sketch to Code, right?
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So, one thing that I do a lot as
I stand up in front of people and
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explain to them the architecture
of Microsoft AI,
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and I always would drive
that drawing would get lost.
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Today, I can now draw it
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and sometimes I'll use
a Surface Hub, right?
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Draw it on a board and then I can
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instantly have that generated into
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HTML and have a webpage or
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a graphic that represents
that that I can reuse.
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It's incredible. But what's most
incredible about it is that,
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that source code is available to me.
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So now, I can even integrate
that into my applications,
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I can access it,
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I can add on top of it,
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I could even contribute to
the project if I want to.
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What an awesome opportunity, right?
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Something that we all
want to try and do.
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So, you'll also see
here Building a Bot,
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right? Drawing Bot, Drones.
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This list of projects
just grows and grows,
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there's teams that are just
dedicated to building innovative,
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fun projects in the AI lab
for you to learn from.
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So, do it. Take a look, right?
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I've shown you three
really interesting areas
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to focus on in order
to learn by doing.
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One is in our GitHub repos,
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there's tons of samples
in there Think about
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your business problem
and then go searching
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for it within the context
of those samples.
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Then, second place is to
go and actually take maybe
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some more formalized classes, right?
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So, if you want to take
a formalized class,
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you could do that in AI School.
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Then, if you're looking
for something that's
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not just in the box of
00:08:45.355 --> 00:08:48.075
pre-built AI or not just
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within some of the models
that you would customize,
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but instead you want to
build your own model,
00:08:53.090 --> 00:08:56.255
we have a whole gallery
of helper projects and
00:08:56.255 --> 00:08:58.010
models that you can leverage in
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order to speed up
your development process.
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Then finally, as you just saw, right?
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So much fun happening in
the AI lab projects that really
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are extremely inspiring to
00:09:07.970 --> 00:09:10.160
look at but more importantly
have the source.
00:09:10.160 --> 00:09:11.420
So, you can go in, grab
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the source and get started
with a cool project.
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So, hopefully, you've
enjoyed today's episode.
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It's just all about the things
that you can dive into.
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We'll be spending future episodes
going into each one of these,
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pulling out a specific project
and getting started.
00:09:24.140 --> 00:09:26.150
So, I thought it'd be
really great if you had
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an opportunity to take a look
around these sites first.
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So, thanks very much for joining
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us and I'll see you
on the next episode